What kind of information do you need to assess progress of community projects that aim to improve livelihoods and biodiversity conservation in remote Conservation Areas in Mozambique? More importantly, how do you efficiently collect this type of data and guarantee the level of consistency and quality needed to make strategic improvements in project implementation?

These are the questions our team faced during our recently concluded Mid-Term Review (MTR) of the World Bank Conservation Areas Development Project (Mozbio)[1]. We learned that there was not more time to wait and by applying the free World Bank-designed Computer Assisted Personal Interviewing (CAPI) Platform Survey Solutions, we could improve data collection and get the Project’s monitoring and evaluation back on track.

The 5-year Mozbio project addresses some of the most pressing challenges to Conservation Areas (CAs) in Mozambique, which covers 25% of the country. Besides strengthening the legal and institutional framework for conservation and promoting nature-based tourism and infrastructure facilities, the cornerstone of the project is to improve livelihood alternatives to local communities that live in and around the CAs. These populations constitute some of Mozambique’s poorest and most vulnerable households. To address this, Mozbio finances small-scale community projects that equip communities with tools to sustainably manage natural resources, engage them in income generating activities and increase their contribution to biodiversity conservation.

Just over half of the rural population in Nepal lives within 2 kilometers of a road in good or fair condition as measured by the Rural Access Index (RAI) in 2015, leaving around 10.3 million rural residents without easy access. The map shows how the RAI varies across the country: in the southern lowlands, where both road and population density are high, the RAI is around 80 percent in some districts. In the more rugged northern regions, lower road density and poor road quality leave many disconnected, resulting in a low RAI figure – in many places less than 20 percent.

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